Pre-print (non-Peer reviewed)

Rodríguez, J., Acuña, J.M., Uratani, J.M., Patón, M. (2020) A mechanistic population balance model to evaluate the impact of interventions on infectious disease outbreaks: Case for COVID19 medRxiv 2020.04.04.20053017; (DOI: 10.1101/2020.04.04.20053017)

Journal Articles (Peer reviewed)

Ahmed, W., Rodríguez, J. (2020) A model predictive optimal control system for the practical automatic start-up of anaerobic digesters Water Research 174, 115599 (DOI: 10.1016/j.watres.2020.115599)
Rafay, R., Uratani, J.M., Hernandez, H.H., Rodríguez, J. (2020) Growth and nitrate uptake in Nannochloropsis gaditana and Tetraselmis chuii cultures grown in sequential batch reactors Front. Mar. Sci. 7:77 (DOI: 10.3389/fmars.2020.00077 )
Scandura, G., Rodríguez, J., Palmisano, G. (2019) A compilation and bioenergetic evaluation of syntrophic microbial growth yields in anaerobic digestion Front. Chem. 7:563 (DOI: 10.3389/fchem.2019.00563)
Patón, M., Rodríguez, J. (2019) A compilation and bioenergetic evaluation of syntrophic microbial growth yields in anaerobic digestion Water Research 159, pp. 176-183 (DOI: 10.1016/j.watres.2019.05.013)
Patón, M., Rodríguez, J. (2019) Integration of bioenergetics in the ADM1 and its impact on model predictions Water Science and Technology 80(2), pp. 339-346 (DOI: 10.2166/wst.2019.279)
Patón, M., González-Cabaleiro, R., Rodríguez, J. (2018) Activity corrections are required for accurate anaerobic digestion modelling Water Science and Technology 77(8), pp. 2057-2067 (DOI: 10.2166/wst.2018.119)
Regueira, A., González-Cabaleiro, R., Ofiţeru, I.D., Rodríguez, J., Lema, J.M. (2018) Electron bifurcation mechanism and homoacetogenesis explain products yields in mixed culture anaerobic fermentations Water Research 141, pp. 349-356 (DOI: 10.1016/j.watres.2018.05.013)
Ahmed, W., Rodríguez, J. (2018) Modelling sulfate reduction in anaerobic digestion: Complexity evaluation and parameter calibration Water Research 130, pp. 255-262 (DOI: 10.1016/j.watres.2017.11.064)
Ahmed, W., Rodríguez, J. (2017) Generalised parameter estimation and calibration for biokinetic models using correlation and single variable optimisations: Application to sulfate reduction modelling in anaerobic digestion Water Research 122, pp.407-418 (DOI: 10.1016/j.watres.2017.05.067)
Perrota, A.R., Kumaraswamy, R., Bastidas-Oyanedel, J.R., Alm, E.J., Rodríguez, J. (2017) Inoculum composition determines microbial community and function in an anaerobic sequential batch reactor. PLoS ONE 12(2): e0171369. (DOI: 10.1371/journal.pone.0171369)
Oyetunde, T., Sarma, P.M., Ahmad, F., Rodríguez, J. (2017) A Multiple Reaction Modelling Framework for Microbial Electrochemical Technologies. International Journal of Molecular Sciences 18(1), 86 (DOI:10.3390/ijms18010086)
Preheim, S.P., Olesen, S.W., Spencer, S.J., Materna, A., Varadharajan, C., Blackburn, M., Friedman, J., Rodríguez, J., Hemond, H., Alm, E.J. (2016) Surveys, simulation and single-cell assays relate function and phylogeny in a lake ecosystem. Nature Microbiology 1, Article number: 16130 (DOI:10.1038/nmicrobiol.2016.130)
Olesen S.W., Vora S., Techtmann S.M., Fortney J.L., Bastidas-Oyanedel J.R., Rodríguez J., et al. (2016) A Novel Analysis Method for Paired-Sample Microbial Ecology Experiments. PLoS ONE 11(5): e0154804. (DOI: 10.1371/journal.pone.0154804)
González-Cabaleiro R, Ofiţeru ID, Lema JM, Rodríguez J (2015) Microbial catabolic activities are naturally selected by metabolic energy harvest rate The ISME Journal, 9(12), pp. 2630-2641. (DOI: 10.1038/ismej.2015.69)
González-Cabaleiro R., Lema J.M., Rodríguez J. (2015) Metabolic Energy-Based Modelling Explains Product Yielding in Anaerobic Mixed Culture Fermentations PLOS ONE, 10(5): e0126739. (DOI: 10.1371/journal.pone.0126739)
García-Gen S., Rodríguez J., Lema J.M. (2015) Control strategy for maximum anaerobic co-digestion performance Water Research (DOI: doi:10.1016/j.watres.2015.05.029)
García-Gen S., Sousbie P., Rangaraj G., Lema J.M., Rodríguez J., Steyer J.P. and Torrijos M. (2014) Kinetic modelling of anaerobic hydrolysis of solid wastes, including disintegration processes Waste Management (DOI: 10.1016/j.wasman.2014.10.012)
García-Gen S., Rodríguez J. and Lema J.M. (2014) Optimisation of substrate blends in anaerobic co-digestion using adaptive linear programming Bioresource Technology 173, pp. 15-167. (DOI: 10.1016/j.biortech.2014.09.089)
Kumaraswamy R., Amha Y.M., Anwar M.Z., Henschel A., Rodríguez J., Ahmad F. (2014) Molecular analysis for screening human bacterial pathogens in municipal wastewater treatment and reuse Environmental Science & Technology (DOI:10.1021/es502546t)
Uratani J.M., Kumaraswamy R., Rodríguez J. (2014) A systematic strain selection approach for halotolerant and halophilic bioprocess development: a review Extremophiles 18(4), pp. 629-639. (DOI: 10.1007/s00792-014-0659-4)
Nwobi A.,Cybulska I.,Tesfai W., Shatilla Y., Rodríguez J., Thomsen M.H. (2014) Simultaneous saccharification and fermentation of solid household waste following mild pretreatment using a mix of hydrolytic enzymes in combination with Saccharomyces cerevisiae. Applied Microbiology and Biotechnology DOI:10.1007/s00253-014-5977-z
González-Cabaleiro R., Lema J.M., Rodríguez J., Kleerebezem R. (2013) Linking thermodynamics and kinetics to assess pathway reversibility in anaerobic bioprocesses Energy Environ. Sci. 6, pp. 3780-3789. (DOI: 10.1039/C3EE42754D)
Sharma M., Jain P., Varanasi J.L., Lal B., Rodríguez J., Lema J.M., Sarma P.M. (2013) Enhanced performance of sulfate reducing bacteria based biocathode using stainless steel mesh on activated carbon fabric electrode. Bioresource Technology 150, pp. 172–180.(DOI:10.1016/j.biortech.2013.09.069)
García-Gen S., Lema J.M. and Rodríguez J. (2013) Generalised modelling approach for anaerobic co-digestion of fermentable substrates. Bioresource Technology 147, pp. 525–533.
Premier GC, Kim JR., Massanet-Nicolau J, Kyazze G, Esteves S, Penumathsa BKV, Rodríguez J, Maddy J, Dinsdale RM, Guwy AJ (2012) Integration of biohydrogen, biomethane and bioelectrochemical systems. Renewable Energy DOI:10.1016/j.renene.2012.01.035
Donoso-Bravo A., Mailier J., Martin C., Rodríguez J., Aceves-Lara C., Vande Wouwer A. (2011) Model selection, identification and validation in anaerobic digestion: A review. Water Research 45(17), pp.5347-5364.
Kim J.R., Rodríguez J., Hawkes F.R., Dinsdale R.M., Guwy A.J., Premier G.C. (2011) Increasing power recovery and organic removal efficiency using extended longitudinal tubular microbial fuel cell (MFC) reactors. Energy & Environmental Science 4, pp. 459–465.
Cubillos G., Arrué R., Jeison D., Chamy R., Tapia E., Rodríguez J. and Ruiz G. (2010) Simultaneous effects of pH and substrate concentration on hydrogen production by acidogenic fermentation. Electronic Journal of Biotechnology (DOI:10.2225/vol13-issue1-fulltext-6)
Kim J.R., Premier G.C., Hawkes FR., Rodríguez J., Dinsdale R. and Guwy A.J. (2010) Modular tubular microbial fuel cells for treatment and energy recovery at low organic loading. Bioresource Technology 101(4), pp.1190-1198.
Rodríguez J., Premier G.C., Guwy A.J., Dinsdale R. and Kleerebezem R. (2009). Metabolic models to investigate energy limited anaerobic ecosystems. Water Science & Technology 60(7) pp.1669–1675.
Rodríguez J., Premier G.C., Dinsdale R. and Guwy A.J. (2009). An implementation framework for wastewater treatment models requiring a minimum programming expertise. Water Science & Technology 59(2), pp 367-380.
Penumathsa B.V.K., Premier G.C., Kyazze G., Dinsdale R., Guwy A.J., Esteves S. and Rodríguez J. (2008). ADM1 can be applied to continuous bio-hydrogen production using a variable stoichiometry approach. Water Research 42(16), pp. 4379-4385.
Rodríguez J., Roca E., Lema J.M. and Bernard O. (2008). Determination of the adequate minimum model complexity required in anaerobic bioprocesses using experimental data. Journal of Chemical Technology and Biotechnology 83(120), pp. 1694-1702.
Rodríguez J., Lema J.M. and Kleerebezem R. (2008). Energy based models for environmental biotechnology. Trends in Biotechnology 26(7), pp. 366-374.
Kleerebezem R., Rodríguez J., Temudo M.F. and van Loosdrecht M.C.M. (2008). Modeling Mixed Culture Fermentations; the role of different electron carriers. Water Science & Technology 57(4), pp.493-497.
Rabaey K., Rodríguez J., Blackall L., Keller J., Batstone D., Verstraete W. and Nealson K.H. (2007). Microbial ecology meets electrochemistry: Electricity driven and driving communities. The ISME Journal 1, pp.9-18.
Rodríguez J., Lema J.M., van Loosdrecht M.C.M. and Kleerebezem R. (2006). Variable stoichiometry with thermodynamic control in ADM1. Water Science & Technology 54(4) , pp. 101-110.
Rodríguez J., Kleerebezem R., Lema J.M., van Loosdrecht M.C.M. (2006) Modelling product formation in mixed culture fermentations. Biotechnology & Bioengineering 93(3), pp.592-606.
Rodríguez J., Ruiz G., Molina F., Roca E. and Lema J.M. (2005). A hydrogen-based variable-gain controller for anaerobic digestion processes. Water Science & Technology 54(2), pp. 57-62.
Bernard O., Chachuat B., Hélias A. and Rodríguez J. (2005). Can we assess the model complexity for a bioprocess? Water Science & Technology 53(1), pp-85-92.
Bernard O., ..., Rodríguez J., et al. (2005). An integrated system to remote monitor and control anaerobic wastewater treatment plants through the internet. Water Science & Technology 52(1-2), pp.457-464.
Carrasco E. F., Rodríguez J., Puñal A., Roca E., Lema J. M. (2004). Diagnosis of acidification states in an anaerobic wastewater treatment plant using a fuzzy-based expert system. Control Engineering Practice 12, pp. 59-64.
Carrasco E. F., Rodríguez J., Puñal A., Roca E., Lema J.M. (2002). Rule-based diagnosis and supervision of a pilot-scale wastewater plant using fuzzy logic techniques. Expert Systems with Applications 22(1), pp.11-20.
Puñal A., Rodríguez J., Carrasco E.F., Roca E., Lema J.M. (2002). Expert system for the on-line diagnosis of anaerobic wastewater treatment plants. Water Science & Technology 45(10), pp.195-200.
Rodríguez J., Carrasco E. F. (2002). Optimization of chemical processes by means of direct search methods. Afinidad LIX, 499, pp.191-198. (In Spanish).
Puñal A., Rodríguez J., Franco A., Carrasco E.F., Roca E., Lema J.M. (2001). Advanced monitoring and control of anaerobic wastewater treatment plants: diagnosis and supervision by a fuzzy-based expert system. Water Science & Technology 43(7), pp.191-198.

Book Chapters (Peer reviewed)

Batstone DJ. and Rodríguez J (2015) Modelling Anaerobic Digestion Processes. In: Fang HHP. And Zhang T.. (eds.) “Anaerobic Biotechnology” Imperial College Press, London 2015. ISBN: 978-1783267903
Rodríguez J. and Premier G.C. (2009) Towards a mathematical description of bioelectrochemical systems. In: Rabaey K., Keller J., Angenent L., Lens P. and Schröder U. (eds.) “Bio-electrochemical systems. From extracellular electron transfer to biotechnological application”. IWA Publishing, London. ISBN 978-1843392330
Zaher U., Rodríguez, J., Franco, A., Vanrolleghem, P.A. (2004) Conceptual approach for ADM1 application. In: Ujang Z. and Henze M. (ed.) "Environmental Biotechnology: Advancement in Water and Wastewater Applications in the Tropics". IWA Publishing. London. ISBN: 978-1843395034
Rodríguez J., Perner I., Schmidt K., Posten C. (2005) Simple metabolic model for Saccharomyces cerevisiae in fed-batch culture to study the cellular nitrogen uptake. In: Pons M-N. and van Impe J. (ed.) "Computer Applications in Biotechnology 2004". Elsevier Science. ISBN: 978-0080442518


Rodríguez J. (2006) Modelling anaerobic Mixed Culture Fermentations. PhD Thesis. Universidade de Santiago de Compostela, Spain
Rodríguez J. (2001) Mathematical modelling of a fed-batch process of Saccharomyces cerevisiae. MSc Thesis. Universität Karksruhe (TH), Germany
Rodríguez J. (1999) Control óptimo de procesos químicos y biotecnológicos mediante algoritmos estocásticos. BEng Project. Universidade de Santiago de Compostela, Spain


Rodríguez J. (2009) Students’ motivation for learning in HE (I): Engaging students in teaching sessions. PGCLT Essay.
Rodríguez J. (2009) Students’ motivation for learning in HE (II): Assessment and inclusivity aspects. PGCLT Essay.

Highlighted publications

Modelling sulfate reduction in anaerobic digestion: Complexity evaluation and parameter calibration

Ahmed W, Rodríguez J
Water Research, 2018; 130, 255-262
DOI: 10.1016/j.watres.2017.11.064
A comparative analysis of five different structures of sulfate reduction (SR) models for anaerobic digestion (AD) was conducted to evaluate their accuracy to provide model developers and users with better information to decide on the optimum degree of complexity. The models evaluated differ in terms of the number/type of sulfate reducing bacterial activities considered based on the electron donors used. A systematic calibration of the evaluated models against a large set of experimental data was also conducted using a very recent parameter calibration method. Results indicate that a simple model incorporating both acetate utilizing and hydrogen utilizing sulfate reducing bacterial activities (the MAH model) achieves a good balance between performance and complexity in terms of prediction errors against experimental data. All the models evaluated provided acceptable predictions except the model including only hydrogen utilizing sulfate reducing bacterial activity. More complex model structures are recommended only if required in specific experimental cases.

Generalised parameter estimation and calibration for biokinetic models using correlation and single variable optimisations: Application to sulfate reduction modelling in anaerobic digestion

Ahmed W, Rodríguez J
Water Research, 2017; 122, 407-418
DOI: 10.1016/j.watres.2017.05.067
In this work, a generalized method for the estimation of biokinetic parameters in anaerobic digestion (AD) models is proposed. The method consists of a correlation-based approach to estimate specific groups of parameters mechanistically, followed by a sensitivity-based hierarchical and sequential single parameter optimisation (SHSSPO) calibration method for the remaining groups of parameters. The method was evaluated to estimate and calibrate the parameter values for sulfate reduction processes when included into the IWA Anaerobic Digestion Model No. 1 (ADM1) and simulations were compared with experimental data from literature. Under the proposed method, a large number of biokinetic parameters, namely biomass yields, maximum specific uptake rates, and half saturation constants, can first be estimated using mechanistic correlations. This achieves a significant reduction in the number of parameters to be fitted to data. For the remaining parameters, a method is proposed based on the overall sensitivity and degree of ubiquity of each parameter to establish a hierarchy in a sequential single parameter optimisation against the experimental data. This approach aims at eliminating the uncertainty on optimality (and therefore parameter identification) associated to multivariable parameter calibration problems. The method was applied to the sulfate reduction related parameters and led to the hydrogen sulfide inhibition parameters as the only ones requiring optimisation against experimental data. Comparison of the proposed SHSSPO performance with that of multi-dimensional parameter optimisation methods shows a superior performance in terms of overall error and computation times. Also, final simulation results led to model predictions of similar, if not better, quality than those achieved by multivariable parameter optimisation methods. The experimental variables optimized for included liquid effluent concentrations of sulfur species and volatile fatty acids as well as effluent gas flows. Overall, the proposed parameter estimation and calibration method provides a deterministic step-by-step approach to parameter estimation that decreases identifiability uncertainty at a very low computational effort. The results obtained suggest that the method could be generically applied with similar success to other biokinetic models frequently used in wastewater treatment.

Inoculum composition determines microbial community and function in an anaerobic sequential batch reactor

Perrotta AR, Kumaraswamy R, Bastidas-Oyanedel JR, Alm EJ, Rodríguez J
PLOS ONE, 2017; 12(2): e0171369
DOI: 10.1371/journal.pone.0171369
The sustainable recovery of resources from wastewater streams can provide many social and environmental benefits. A common strategy to recover valuable resources from wastewater is to harness the products of fermentation by complex microbial communities. In these fermentation bioreactors high microbial community diversity within the inoculum source is commonly assumed as sufficient for the selection of a functional microbial community. However, variability of the product profile obtained from these bioreactors is a persistent challenge in this field. In an attempt to address this variability, the impact of inoculum on the microbial community structure and function within the bioreactor was evaluated using controlled laboratory experiments. In the course of this work, sequential batch reactors were inoculated with three complex microbial inocula and the chemical and microbial compositions were monitored by HPLC and 16S rRNA amplicon analysis, respectively. Microbial community dynamics and chemical profiles were found to be distinct to initial inoculate and highly reproducible. Additionally we found that the generation of a complex volatile fatty acid profile was not specific to the diversity of the initial microbial inoculum. Our results suggest that the composition of the original inoculum predictably contributes to bioreactor community structure and function.

A Multiple Reaction Modelling Framework for Microbial Electrochemical Technologies

Oyetunde T, Sarma PM, Ahmad F, Rodríguez J
International Journal of Molecular Sciences, 2017; 18(1), 86
DOI: 10.3390/ijms18010086
A mathematical model for the theoretical evaluation of microbial electrochemical technologies (METs) is presented that incorporates a detailed physico-chemical framework, includes multiple reactions (both at the electrodes and in the bulk phase) and involves a variety of microbial functional groups. The model is applied to two theoretical case studies: (i) A microbial electrolysis cell (MEC) for continuous anodic volatile fatty acids (VFA) oxidation and cathodic VFA reduction to alcohols, for which the theoretical system response to changes in applied voltage and VFA feed ratio (anode-to-cathode) as well as membrane type are investigated. This case involves multiple parallel electrode reactions in both anode and cathode compartments; (ii) A microbial fuel cell (MFC) for cathodic perchlorate reduction, in which the theoretical impact of feed flow rates and concentrations on the overall system performance are investigated. This case involves multiple electrode reactions in series in the cathode compartment. The model structure captures interactions between important system variables based on first principles and provides a platform for the dynamic description of METs involving electrode reactions both in parallel and in series and in both MFC and MEC configurations. Such a theoretical modelling approach, largely based on first principles, appears promising in the development and testing of MET control and optimization strategies.

Microbial catabolic activities are naturally selected by metabolic energy harvest rate

González-Cabaleiro R, Ofiţeru ID, Lema JM, Rodríguez J
The ISME Journal, 2015; 9(12), 2630-2641
DOI: 10.1038/ismej.2015.69
The fundamental trade-off between yield and rate of energy harvest per unit of substrate has been largely discussed as a main characteristic for microbial established cooperation or competition. In this study, this point is addressed by developing a generalized model that simulates competition between existing and not experimentally reported microbial catabolic activities defined only based on well-known biochemical pathways. No specific microbial physiological adaptations are considered, growth yield is calculated coupled to catabolism energetics and a common maximum biomass-specific catabolism rate (expressed as electron transfer rate) is assumed for all microbial groups. Under this approach, successful microbial metabolisms are predicted in line with experimental observations under the hypothesis of maximum energy harvest rate. Two microbial ecosystems, typically found in wastewater treatment plants, are simulated, namely: (i) the anaerobic fermentation of glucose and (ii) the oxidation and reduction of nitrogen under aerobic autotrophic (nitrification) and anoxic heterotrophic and autotrophic (denitrification) conditions. The experimentally observed cross feeding in glucose fermentation, through multiple intermediate fermentation pathways, towards ultimately methane and carbon dioxide is predicted. Analogously, two-stage nitrification (by ammonium and nitrite oxidizers) is predicted as prevailing over nitrification in one stage. Conversely, denitrification is predicted in one stage (by denitrifiers) as well as anammox (anaerobic ammonium oxidation). The model results suggest that these observations are a direct consequence of the different energy yields per electron transferred at the different steps of the pathways. Overall, our results theoretically support the hypothesis that successful microbial catabolic activities are selected by an overall maximum energy harvest rate.

Metabolic Energy-Based Modelling Explains Product Yielding in Anaerobic Mixed Culture Fermentations

González-Cabaleiro R, Lema JM, Rodríguez J
PLOS ONE, 2015; 10(5): e0126739
DOI: 10.1371/journal.pone.0126739
The fermentation of glucose using microbial mixed cultures is of great interest given its potential to convert wastes into valuable products at low cost, however, the difficulties associated with the control of the process still pose important challenges for its industrial implementation. A deeper understanding of the fermentation process involving metabolic and biochemical principles is very necessary to overcome these difficulties. In this work a novel metabolic energy based model is presented that accurately predicts for the first time the experimentally observed changes in product spectrum with pH. The model predicts the observed shift towards formate production at high pH, accompanied with ethanol and acetate production. Acetate (accompanied with a more reduced product) and butyrate are predicted main products at low pH. The production of propionate between pH 6 and 8 is also predicted. These results are mechanistically explained for the first time considering the impact that variable proton motive potential and active transport energy costs have in terms of energy harvest over different products yielding. The model results, in line with numerous reported experiments, validate the mechanistic and bioenergetics hypotheses that fermentative mixed cultures products yielding appears to be controlled by the principle of maximum energy harvest and the necessity of balancing the redox equivalents in absence of external electron acceptors

A systematic strain selection approach for halotolerant and halophilic bioprocess development: a review

Uratani JM, Kumaraswamy R, Rodríguez J
Extremophiles, 2014 Jul; 18(4):629-639.
DOI: 10.1007/s00792-014-0659-4
Halotolerant and halophilic microorganisms have potential applications in a number of very relevant environmental and industrial bioprocesses, from wastewater treatment to production of value-added chemicals. While numerous microbial strains have been identified and studied in the literature, the number of those successfully used in industrial applications is comparatively small. Literature is abundant in terms of characterisation of specific strains under a microbiology perspective; however, there is a need for studies tackling the selection of strains for bioprocess applications. This review presents a database of over 200 halophilic and halotolerant prokaryote strains compiled from taxonomic microbiological resources and classified by trophic groups as well as by their salinity, pH and temperature tolerance and optimum ranges, all under a process development perspective. In addition to this database, complementary systematic approaches for the selection of suitable strains for a given trophic activity and environmental conditions are also presented. Both the database and the proposed selection approaches together constitute a general tool for process development that allows researchers to systematically search for strains capable of specific substrate degradations under specific conditions (pH, T, salinity). Many exiting established halotolerant and halophilic environmental and industrial bioprocesses appear to have been developed following strategies in line with the systematic approaches proposed here.